Automated loan risk assessment system and method

ABSTRACT

An automated loan risk assessment system and method are described. The system is adapted to receive information about a loan or an insurance application requesting insurance to cover same. The system calculates a risk score for the loan based on a plurality of risk factors including at least two of a fraud risk factor, a credit risk factor and a property valuation risk factor. The risk score can be used by a loan service provider in deciding whether or not to fund or insure the loan.

CROSS REFERENCE TO RELATED APPLICATION

This is a continuation-in-part of application Ser. No. 09/993,072entitled Predatory Lending Detection System and Method Therefor filedNov. 13, 2001 now U.S. Pat. No. 7,689,503.

FIELD OF THE INVENTION

This invention relates to an automated loan risk assessment system andmethod and in particular, an automated system and method of assessingrisk with respect to a loan based on a plurality of risk factorsincluding at least two of a fraud risk factor, an underwriting riskfactor and a property valuation risk factor.

BACKGROUND OF THE INVENTION

One of the American dreams is home ownership. However, according to theMortgage Guaranty Insurance Company, “[r]elative to the growth in homeprices over the last century, Americans are earning less and, as aresult, saving less.” As a result, the down payment required to secure amortgage often prevents young individuals just “starting out” frombuying a home. Consequently, home mortgages having low down paymentshave become very popular. The less money a borrower has invested in ahome, however, the greater the risk of default. Therefore, while thereis some risk that a borrower may default with a conventional mortgagewhich typically requires a twenty percent (20%) down payment, this riskis increased for borrowers who are only putting down five percent (5%)or ten percent (10%). Low down payment mortgages, therefore, oftenrequire that the borrower obtain some type of mortgage insurance toprotect the lender against loss if the borrower defaults on themortgage. However, even with such protection, the lender typically isnot able to recoup the entire amount of the mortgage.

Lenders and mortgage insurers try to minimize their exposure byobtaining information on borrowers indicative of their risk ofdefaulting on a mortgage, such as through credit reports or mortgageservice systems such as The Mortgage Office, MORESERV and TRAKKER. Thereare also several existing consumer and mortgage scoring systems whichgenerate underwriting scores to assist mortgage insurers in this regard,such as for example, the Fair Issac Consumer (FICO) score, the PrivateMortgage Insurance (PMI) aura score, the United Guaranty ACUscore, andthe ARCS subprime mortgage score.

None of these scoring tools, however, assess risk attributable to fraud(i.e., data integrity). For example, a lender may manipulate the loaninformation to qualify an otherwise unqualified borrower, or a borrowermay falsify income or employment information in order to obtain theloan. To the extent fraudulent claims are not detected, the costsassociated with paying them are ultimately borne by the consumer.According to a Sep. 26, 2001 article in Realty Times, reports ofpossible fraudulent activity in connection with a mortgage increasedfifty-seven percent (57%) in the first quarter of this year.

Fraud can originate from numerous sources, such as lenders, borrowers,appraisers, title agents, real estate agents and builders. Fraud can beinjected into the loan process in a number of ways, such as through theuse of false credit histories, false income/employment information,falsified appraisals, inflated property values and false identification.For example, loan officers might fabricate pay stubs to help a borrowerqualify for a loan that the borrower might not otherwise qualify for sothat he or she can collect a commission. Likewise, a borrower mightsubmit falsified tax returns to ensure he or she qualifies for the loan.

The potential for fraud increases as the number of parties involved inthe transaction increases. Increases in mortgage fraud are also due to anumber of other factors, such as (1) the creation of new and creativeforms of financing, coupled with automated underwriting, (2) theincreased availability of personal information via the Internet, and (3)the low-cost of computer equipment such as printers and copiers thatproduce high quality copies such that one can fabricateauthentic-looking documents (i.e., pay stubs, tax returns).

Not only do fraudulent loans result in enormous financial losses,misrepresenting information on a loan application is illegal. Moreover,penalties for fraudulent lending violations include substantial monetarypenalties such as repayment of twice the amount of all interest, fees,discounts and charges as well as court and attorney fees to theborrower. In addition, such violations can result in the temporary orpermanent suspension of business privileges of the lender, such as theability to sell to quasi-governmental agencies (e.g., Freddie Mac andFannie Mae) or in secondary markets, or the ability to sell certaintypes of loans. In some cases, lenders can lose their licenses and faceimprisonment. In the secondary market, purchasers and assignees can beheld liable for all claims on loans in their possession. These costs arethen often passed on to consumers in the form of higher loan costs,higher lending fees and higher interest rates.

Yet another risk associated with funding or insuring a loan relates tothe accuracy of the valuation of the subject property. One of the mostcommon problems associated with property valuations is known as propertyflipping. This practice involves a property that is bought and thenresold (i.e., flipped) several times, each time at a falsely inflatedprice. The property is then sold to an unsuspecting mortgage companythat pays much more for the property than its market value that canresult in a substantial loss to the mortgage lender upon the resellingof the property. Typically, lenders use internal or third party propertyvaluation models or tools such as AppIntell, Inc.'s ValVerify, CaseShiller Weiss' CASA, Solimar's Basis100 or First American's productsuite which includes Value Point, Home Price Index, Assessed ValueModel, AREA's, and Value Point Plus to analyze the value of the propertyprovided in the loan documents and score it based on its accuracy. Suchan analysis looks at factors like the value of other properties aroundthe location of the subject property and the selling prices ofcomparable properties. This score is usually in the form of a value orgrade representing a confidence level, which corresponds to a range ofpredicated value. For example, in the case of CASA, Grade A refers to apredicted value range within 6%, Grade B refers to a predicted valuerange between 6% and 8%, Grade C refers to a predicted value range ofbetween 8% and 10%, Grade D refers to a predicted value range between10% and 14%, and Grade E refers to a predicted value range between 14%and 20%. The bigger the discrepancy between the property value providedin the loan documents and the property value determined by such modelsor tools, the greater the risk in funding or insuring the loan.

Currently, fraud, underwriting and property valuation scoring systemsoriginate from different sources. As a result, they are not compatiblewith each other. In other words, mortgage service providers must go toone company to have a risk assessment of the loan from an underwritingperspective, a different company to have a risk assessment of the loanfrom a fraud perspective, and possibly yet a different company to have arisk assessment of the loan from a property valuation perspective. Thiscumbersome process not only significantly delays the underwritingprocess, but also increases its costs tremendously. In fact, the singlelargest insurance policy acquisition cost in mortgage insurance iscontract underwriting. Approximately half of loan public filings byprivate mortgage insurers in 2000 were referred to underwriters formanual review after the loan was scored vis-à-vis the borrower's credithistory. Moreover, since the scores are not compatible, they cannot becombined into an overall score reflecting the level of risk of fundingor insuring a loan based on at least two of the three scores. Thepotential cost and time savings as well as value of an automatic riskassessment system that takes into account risk from at least two of afraud, underwriting and property valuation perspective all provided fromone source is enormous.

There is, therefore, a need for an automated system and method thatassesses the risk associated with funding or insuring a loan based on aplurality of risk factors.

BRIEF SUMMARY OF THE INVENTION

It is in view of the above problems that the present invention wasdeveloped. In particular, an automated loan risk assessment system isdisclosed which comprises a mechanism for receiving information about aloan, and a mechanism for calculating a risk score for the loan based ona plurality of risk factors including at least two of a fraud riskfactor, an underwriting risk factor and a property valuation riskfactor, whereby the risk score can be used by a loan service provider indeciding whether or not to fund or insure the loan. In one embodiment,the risk score is based on a combination of the fraud risk score factor,the underwriting risk factor and the property valuation risk factor.

The risk calculation mechanism may further comprise a mechanism forcalculating a fraud risk score, a mechanism for calculating anunderwriting risk score, and a mechanism for calculating a propertyvaluation score, wherein the risk score for the loan is based on atleast two of the fraud risk score, the underwriting risk score and theproperty valuation risk score. The fraud risk score calculationmechanism comprises a mechanism for storing general information aboutborrowers and properties, and a mechanism for detecting one or morevariances among the loan information or between the loan information andthe general information, each variance having a certain degree, suchthat the fraud risk score is based on the detected variances and thedegrees thereof. The system may further comprise a mechanism fordetermining one or more steps needed to resolve the one or more detectedvariances, a mechanism for tracking the status of the one or moredetected variances, and/or a mechanism for assigning a risk category tothe loan based on the risk score.

The underwriting risk score calculation mechanism comprises means forobtaining the underwriting risk score from an underwriting risk scoreprovider, the property valuation risk score calculation mechanismcomprises means for obtaining a property valuation risk score from aproperty valuation score provider. The system further comprises amechanism for converting at least one of the fraud risk score, theunderwriting risk score and the property valuation risk score. In oneembodiment, the converting mechanism comprises a mechanism for weightingat least one of the fraud risk score, the underwriting risk score andthe property valuation risk score based on the level of risk associatedtherewith such that the risk score is based on the weights assignedthereto. In another embodiment, the mechanism for converting comprises amechanism for converting at least one of the fraud risk score, theunderwriting risk score and the property valuation risk score such thatall of the scores are compatible, and wherein the risk score representsan average of the compatible scores.

The loan information may include insurance information related to atleast one insurance claim being asserted against an insurance policy towhich a loan is subject, such that the mechanism for calculating a riskscore comprises a mechanism for calculating a risk score for the claimbased on a plurality of risk factors including at least one of a fraudrisk factor, an underwriting risk factor and a property valuation riskfactor, whereby the risk score can be used by a loan service provider indeciding whether to allow or deny the claim.

The system may further comprise a mechanism for interfacing at least onepricing scheme of a loan service provider such that a loan or aninsurance policy for a loan can be automatically priced based on therisk score calculated therefor.

The present invention also discloses a computer-readable medium whosecontents cause a computer system to assess the risk associated withfunding or insuring a loan by performing the steps of receivinginformation about a loan, and calculating a risk score for the loanbased on a plurality of risk factors including at least two of a fraudrisk factor, a credit risk factor and a property valuation risk factor.The step of calculating the risk score further comprises the steps ofcalculating a fraud risk score, calculating an underwriting risk score,and calculating a property valuation score, wherein the risk score forthe loan is based on the fraud risk score, the underwriting risk scoreand the property valuation risk score. In one embodiment, the risk scoreis based on a combination of the fraud risk score, the underwriting riskscore and the property valuation risk score.

The step of calculating the fraud risk score may comprise storinggeneral information about borrowers and properties, and detecting one ormore variances among the loan information or between the loaninformation and the general information, each variance having a certaindegree, such that the fraud risk score is based on the detectedvariances and the degrees thereof. In one embodiment, the mediumincludes the step of calculating a variance score for each detectedvariance based on the degree thereof, wherein the fraud risk scorerepresents the sum of the variance scores. The medium may furtherinclude the steps of determining one or more steps needed to resolve theone or more detected variances, tracking the status of the one or moredetected variances, and/or assigning a risk category to the loan basedon the risk score.

The step of calculating the underwriting risk score may compriseobtaining the underwriting risk score from an underwriting risk scoreprovider, and the step of calculating the property valuation risk scoremay comprise obtaining a property valuation risk score from a propertyvaluation score provider. The medium may further comprise the step ofconverting at least one of the fraud risk score, the underwriting riskscore and the property valuation risk score. In one embodiment, the stepof converting comprises weighting at least one of the fraud risk score,the underwriting risk score and the property valuation risk score basedon the level or risk associated therewith such that the risk score isbased on the weights assigned thereto. In another embodiment, the stepof converting comprises converting at least one of the fraud risk score,the underwriting risk score and the property valuation risk score suchthat all of the scores are compatible, and averaging the compatiblescores.

The loan information includes insurance information related to at leastone insurance claim being asserted against an insurance policy to whicha loan is subject, such that the medium further comprises the step ofcalculating a risk score for the claim based on a plurality of riskfactors including at least one of a fraud risk factor, an underwritingrisk factor and a property valuation risk factor, whereby the risk scorecan be used by a loan service provider in deciding whether to allow ordeny the claim.

The medium may further comprise the step of interfacing at least onepricing scheme of a loan service provider such that a loan or aninsurance policy can be automatically priced based on the risk scorecalculated therefor.

The present invention also discloses a computer-implemented method ofassessing the risk associated with the funding or insuring of a loan.The method comprises receiving information about a loan, and calculatinga risk score for the loan based on a plurality of risk factors includingat least two of a fraud risk factor, an underwriting risk factor and aproperty valuation risk factor. The step of calculating the risk scorecomprises the steps of calculating a fraud risk score, calculating anunderwriting risk score, and calculating a property valuation score,wherein the risk score for the loan is based on the fraud risk score,the underwriting risk score and the property valuation risk score. Inone embodiment, the risk score is based on a combination of the fraudrisk score, the underwriting risk score, and the property valuation riskscore. The step of calculating the fraud risk score comprises storinggeneral information about borrowers and properties, and detecting one ormore variances among the loan information or between the loaninformation and the general information, each variance having a certaindegree, such that the fraud risk score is based on the detectedvariances and the degrees thereof. In one embodiment, the method furthercomprises the step of calculating a variance score for each detectedvariance based on the degree thereof, wherein the fraud risk scorerepresents the sum of the variance scores. The method may furthercomprise the steps of determining one or more steps needed to resolvethe one or more detected variances, tracking the status of the one ormore detected variances, and/or assigning a risk category to the loanbased on the risk score.

The step of calculating the underwriting risk score comprises obtaininga credit risk score from a credit risk score provider, and the step ofcalculating the property valuation risk score comprises obtaining aproperty valuation risk score from a property valuation score provider.The method may further comprise the step of converting at least one ofthe fraud risk score, the underwriting risk score and the propertyvaluation risk score. In one embodiment, the step of convertingcomprises weighting at least one of the fraud risk score, theunderwriting risk score and the property valuation risk score based onthe level of risk associated therewith such that the risk score is basedon the weights assigned thereto. In another embodiment, the step ofconverting comprises converting at least one of the fraud risk score,the underwriting risk score and the property valuation risk score suchthat all of the scores are compatible, and averaging the compatiblescores.

The loan information includes insurance information related to at leastone insurance claim being asserted against an insurance policy to whichthe loan is subject, such that the step of calculating a risk scorecomprises calculating a risk score for the claim based on a plurality offactors including at least one of a fraud risk factor, an underwritingrisk factor, and a property valuation risk factor, whereby the riskscore can be used by a loan service provider in deciding whether toallow or deny the claim.

The method may further comprise the step of interfacing at least onepricing scheme of a loan service provider such that a loan or insurancepolicy can be automatically priced based on the risk score calculatedtherefor.

BRIEF DESCRIPTION OF THE SEVERAL VIEWS OF THE DRAWINGS

The accompanying drawings, which are incorporated in and form a part ofthe specification, illustrate the embodiments of the present inventionand together with the description, serve to explain the principles ofthe invention. In the drawings:

FIG. 1 is a block diagram of a loan risk assessment system in accordancewith one embodiment of the present invention.

FIG. 2 is a flowchart illustrating one embodiment of the steps forassessing the risk associated with a loan based on fraud using thesystem of FIG. 1.

FIG. 3 shows one embodiment of an input screen display generated by thesystem and method of the present invention.

FIG. 4 is a flowchart illustrating one embodiment of the steps forassessing the risk associated with a loan based on a combination offraud, underwriting and property valuation risk factors using the systemof FIG. 1.

FIG. 5 shows one embodiment of a report generated by the system andmethod of the present invention.

DETAILED DESCRIPTION OF THE INVENTION

FIG. 1 shows a block diagram of a system 10 in accordance with oneembodiment of the present invention; namely the assessment of riskassociated with insuring a mortgage based on a plurality of risk factorsincluding without limitation a fraud risk factor, an underwriting riskfactor and a property valuation risk factor. While the system 10 will bedescribed in connection with the insurance of a mortgage, it can beappreciated that the system 10 can be applied to the funding or insuringof any type of loan. The system 10 consists of a plurality of databasesfor storing a plurality of different types of information. Inparticular, a database 12 stores a variety of specific informationrelated to the loan, including without limitation information about theborrower and the subject property. Such information may come from avariety of documents including without limitation an insuranceapplication 1, an Escrow Waiver 3, an Adjustable Rate Note 5, anItemization of Amount Financed 7, a U.S. Department of Housing and UrbanDevelopment (HUD) I Settlement statement 9, an Adjustable Rate Note 11,a Special Closing Instructions document 13, a Truth-in-Lending statement15, a loan document worksheet 17, a Deed of Trust 19, and a residentialloan application 21 (also known as a “1003”). To the extent the system10 is also or alternatively being used to assess the risk associatedwith insuring a loan, the loan information may include informationrelated to the insurance of the loan. Such information may come from theinsurer and the insurance application.

A database 14 stores general information related to borrowers, lenders,insurers, properties and any other aspect of the loan. Borrowerinformation may include personal information about the borrower such ashis or her name, address, and Social Security number. Lender informationmay include the lender's name, address and lending history. Propertyinformation may include addresses and appraisal values. This generalinformation can come internally from the operator of the system 10,and/or from one or more third party or external database sources. Forexample, property information could come from such third party sourcesas International Data Management Corporation (IDM), Data Quick andManagement Risk Assessment Corporation (MRAC), and Accumail UnitedStates Postal Service National Database. Borrower and lender informationcould come from third party sources, such as Trans Union, Equifax, LexisNexis, Acxiom, Info USA and Dunn and Bradstreet.

The loan information and the general information are stored in adatabase server 16, which includes communication software forcommunicating with third party or external databases not stored therein.It can be appreciated, however, that the loan information and thegeneral information could be each stored in a separate database serveror stored in various combinations thereof as needed. In one embodiment,the server database 16 is a Dell Power-Edge 2400 running Sequel Server2000 software in a Windows 2000 operating system environment. In apreferred embodiment, two database servers are provided for loadbalancing and redundancy.

The loan information may be input into system 10 for storage in loandatabase 12 via input devices 18. While input devices 18 as shown arepersonal computers, they can be any type of device that allows the inputof data. Specifically, the insurer logs on to system 10 through an inputdevice 18, whereupon several screens such as screen 50 shown in FIG. 3,are displayed. Each screen 50 may include one or more fields in whichthe loan information can be input. For example, screen 50 includes aGeneral Information section 52 in which general information about theborrower can be input, such as last name, middle name, first name,Social Security number, phone number, age and citizenship. Currentresidence section 54 allows the insurer to input information related tothe borrower's current residence. Employer Information sections 56 and58 allow the insurer to input information related to a borrower'scurrent and previous employers. Once the information has been input, theinsurer can save it by clicking on the “Save Data” button 60. If theinsurer does not wish to save the information, he or she can simplyclick the “Cancel” button 62. Similar screens are displayed to theinsurer until all of the necessary loan information has been input. Onceinput, the loan information can be downloaded to loan database 12.

Input devices 18 are shown as being located at the insurer'sestablishment such that the loan information is input directly by theinsurer and then simply downloaded to database server 16 for storage inthe loan database 12. The insurer may in turn use a document preparationcompany or rely on the lender to input and download some or all of theloan information directly for storage in loan database 12.Alternatively, the loan information can be sent to the operator of thesystem 10 to be input via one or more input devices 20 connected eitherdirectly or remotely to an application server 22. Such input devices 20may then also be used to input any general information to be stored ingeneral database 14. The loan information may be input to system 10 by alender in the same manner as described above with respect to theinsurer. One or more of the input devices 18 or 20 may be connected to aprinter 24 for printing reports generated by the system 10.

Application server 22 is responsible for processing the loan informationassociated with each loan or insurance application to assess the levelof risk associated with the funding and/or insuring of the loan,respectively. Application server 22 includes memory (not shown) forstoring the program or programs necessary for assessing such risk aswill be further discussed herein. Application server 22 interfaces withthe input devices 18, underwriting scoring systems 30, and propertyvaluation systems 32 through server 28. The connection between server 28and input devices 18, underwriting scoring systems 30, and propertyvaluation systems 32 can be via any communication network such as thetelephone network, a satellite network, a cable network or any othercommunications network capable of transmitting information across it.Server 28 includes communication software to allow it to communicatewith input devices 18, underwriting scoring systems 30, and propertyvaluation systems 32. In one embodiment, application server 22 andserver 28 are Dell Power-Edge 1550 servers running Microsoft InternetInformation Services (IIS) Server v5.0 software under a Windows 2000advanced server operating system. In a preferred embodiment, server 28is a web server that allows system 10 to be implemented through awebsite accessible via the Internet. However, it can be appreciated thatany type of server having the necessary processing capabilities andstorage capacity may be used. In a preferred embodiment, applicationserver 22 and server 28 are provided in duplicate for load balancing andredundancy.

The process of assessing the level of risk associated with insuring aloan will be described with reference to FIGS. 2, 4 and 5. For exemplarypurposes, this process will be discussed in connection with a system 10that is web-based and accessed by a mortgage insurer. It can beappreciated, however, that the system 10 need not be web-based tooperate, and any loan service provider with authorized access to thesystem 10 and who desires the ability to automatically assess the riskassociated with the funding and/or insuring of a loan may use the system10.

FIG. 2 illustrates the process of assessing the risk of insuring amortgage based on the fraud risk factor. At 100, information about theloan requesting to be insured is input. At 102, application server 22checks this loan information to determine if there are any variances ordifferences among the loan information stored in loan database 12 orbetween the loan information stored in loan database 12 and the generalinformation stored in general information database 34. For example, inthe case of falsified identity, the social security number provided ischecked to see if it corresponds to someone who has died, if it has beenreported stolen, if it was issued prior to the borrower's birth year, orit if does not match the borrower's age. If no variances are found, at105 the system 10 scores the loan accordingly.

If one or more variances are found, at 106, the system 10 preferablyscores each variance based on the degree thereof. In one embodiment, thescore is a numeric value such that the higher the degree of variance,the lower the score. For example, a discrepancy in the borrower'saddress may be scored lower (i.e., worse) than a discrepancy in theemployer's address. It can be appreciated, however, that a reversescoring system could be used whereby a higher degree of variance resultsin a higher score. It can also be appreciated that any type of scoringsystem indicative of the severity of the risk associated with thedetected variance, including a non-numeric one, could be used. Forexample, each detected variance can be assigned a specific weight orgrade based on its severity. Likewise, the system 10 can calculate afraud score (as discussed below) based on the type, number and severityof the detected variances rather than scoring each variance separately.

At 108, the system 10 calculates a fraud score based on the sum of thescores of each detected variance and at 110, assigns the loan a riskcategory based on the fraud score. In one embodiment, a total scoreranging between 600 and 1000 results in a “Pass” score, a total scoreranging between 401 and 599 results in a “High” score, and a total scoreranging between 0 and 400 results in an “Investigate” score. A Passscore means that there were no or minimal variances detected inconnection with the loan information and that therefore, there is noactual fraud detected in connection with this loan. A High score meansthat the variances detected indicate a potential for fraud and thattherefore while there is a relatively low level of risk of insuring theloan vis-à-vis fraud, the insurer may nevertheless want to furtherscrutinize the loan information. An Investigate score means that thereis some aspect of the loan that is potentially fraudulent, but a greaterlevel of risk than in the case of a High score. Again, any type ofscoring system indicative of the risk associated with the loaninformation at issue may be used.

At 112, the system 10 determines what step or steps are needed toresolve any detected variances, and at 114, the system 10 notifies theuser of the results. FIG. 5 shows one embodiment of how system 10 maynotify a user of its results. Specifically, a screen 70 is displayed tothe user on his or her input device 18. In section 72, identifyinginformation about the loan is displayed, such as the name of theborrower and the loan number. In section 74, more detailed loaninformation is provided, such as for example the loan amount, thepurchase price and the estimated/appraised value. Section 76 providesinformation from the insurance application. Section 76 provides asummary of the results of the insurance application as processed bysystem 10. At 78, the total fraud score is displayed, and at 80, therisk category (i.e., Pass, High or Investigate) is identified.

In the case of an Investigate status, section 82 identifies eachvariance or transgression and at 84, provides a description of thevariance. In the example shown, the first transgression indicates thatthe property value exceeds its expected range. The second transgressionindicates that the effective date on the insurance application does notreflect the loan closing date. At 86, the system 10 identifies anyaction that can be taken to resolve the transgression. A section 88 isalso preferably provided which allows any additional comments regardingthe transgression, as well as a section 90 which allows the user totrack the status of a transgression and if and when it has beenresolved. Alternatively, in the case where the insurance application isnot being processed in real-time, notification can be sent to the uservia e-mail, facsimile, telephone or any other known notification method.

FIG. 4 illustrates the process of assessing the level of risk associatedwith insuring a loan vis-à-vis a combination of the fraud, underwritingand property value risk factors. In particular, at 200, informationabout the loan requesting to be insured is input into system 10. At 202,application server 22 checks this loan information to determine if thereare any variances among the loan information stored in loan database 12or between the loan information stored in loan database 12 and thegeneral information stored in general database 34. If no variances aredetected, at 204 the system 10 scores the loan. If one or more variancesare detected, at 206, the system 10 scores each variance based on thedegree thereof. As stated previously herein, any scoring mechanism maybe used. At 208, the system 10 calculates a fraud score for eachinsurance application based on the sum of the scores of each detectedvariance. As previously mentioned, in the case where each detectedvariance is not individually scored, the fraud score is based on thenumber, type and severity of detected variances. At 210, the system 10obtains an underwriting score from an underwriting scoring system 30. At212, the system 10 obtains a property valuation score from a propertyvaluation system 32. At 214, the system 10 calculates a combined scorebased on a combination of the fraud, underwriting and property valuationscores.

Step 214 is performed by combining the three scores based on eachindividual score and the level of risk associated therewith. Fordiscussion purposes only, it will be assumed that the fraud and propertyvaluation scores are Pass, High or Investigate, and the underwritingscore is one generated from a Fannie Mae underwriting system whichincludes the following: approve/eligible, approve/ineligible,refer/eligible, refer/ineligible, refer with caution or out of scope(i.e., reject). It will also be assumed that the combined scorecalculated by the system 10 will be the same as that used by theunderwriting scoring system.

In one embodiment, the incompatible scores are “converted” by system 10by assigning a weight to each individual score vis-à-vis the otherscores and its corresponding level of risk. For example, a fraud scoreof Investigate will always be weighted such that the combined score willalways be an Out of Scope score regardless of the underwriting andproperty valuation scores. Likewise, a property valuation score ofInvestigate will also always be weighted such that the combined scorewill always be an Out of Scope score regardless of the fraud andproperty valuation scores. In the case where there are no Investigatescores but at least one of the fraud or property valuation scores isHigh, the combined score will be Refer with Caution. In general, theless risk associated with each score, the better the combined score.

Alternatively, one or more of the scores are converted into a score thatis compatible with the other. For example, the numeric fraud score canbe used as the scoring system for the combined score and theunderwriting and property valuation scores can be converted to a similarnumeric value representative thereof. One advantage of using the numericscores is that the level of risk is more specific. For instance, while ascore of 401 and a score of 599 would both be High, the score 401represents a higher risk than the score 599. Under such a system, anapprove/eligible score will have a higher (i.e., better) score than arefer with caution score. Each score can then be added together and anaverage score computed. It can be appreciated, that any scoring systemcan be used for the combined score and that any fraud, underwritingand/or property valuation scores not compatible therewith would need tobe “converted” by system 10 before the combined score could becalculated.

At 216, the system 10 assigns a risk category to the loan based on thecombined score. In a preferred embodiment, at 218, the system 10determines the steps needed to resolve any detected variances. At 220,the system 10 notifies the user of the results, and at 222 the processends.

While the system and method have been described with respect to theassessment of risk based on the fraud score by itself, and a combinationof the fraud, underwriting and property valuation scores, it can beappreciated that the system and method of the present invention canincorporate any combination of these scores (i.e., fraud score plusunderwriting score, fraud score plus property valuation score, orunderwriting plus property valuation score). With such a system andmethod, a loan service provider can better assess the level of riskinvolved with funding or insuring the loan through one source.

The system and method of the present invention can also be used toassist insurers with the processing of claims associated with theirinsurance policies. The system is the same in structure as system 10shown in FIG. 1, except that the loan database 12 includes informationinput by the insurer related to the claims and corresponding insurancepolicies at issue and each insured's payment history for the policy. Aninsurer can determine whether to accept or deny a claim depending on atleast one of a fraud risk score, and underwriting risk score, a propertyvaluation risk score or a combined score calculated by the system forthe claim at issue.

Finally, the system and method of the present invention can also be usedas an automatic risk-pricing tool to assist loan service providers withthe pricing of loans and insurance policies, respectively. Specifically,since the combined score is representative of the risk associated withthe loan or insurance application, it can be used to price the loan orinsurance policy covering it. In particular, server 28 of FIG. 1interfaces the lender's or insurer's pricing scheme (not shown), suchthat the loan or insurance policy at issue can be automatically pricedout based on the combined score calculated therefor.

In view of the foregoing, it will be seen that the several advantages ofthe invention are achieved and attained. The embodiments were chosen anddescribed in order to best explain the principles of the invention andits practical application to thereby enable others skilled in the art tobest utilize the invention in various embodiments and with variousmodifications as are suited to the particular use contemplated. Asvarious modifications could be made in the constructions and methodsherein described and illustrated without departing from the scope of theinvention, it is intended that all matter contained in the foregoingdescription or shown in the accompanying drawings shall be interpretedas illustrative rather than limiting. Thus, the breadth and scope of thepresent invention should not be limited by any of the above-describedexemplary embodiments, but should be defined only in accordance with thefollowing claims appended hereto and their equivalents.

We claim:
 1. An automated loan risk assessment system, comprising: meansfor receiving information about a loan; means for detecting a pluralityof variances associated with the information about the loan; means forscoring each variance detected by the means for detecting the pluralityof variances; means for calculating a numeric risk score for the loanbased on a plurality of risk factors including at least two of a fraudrisk factor, an underwriting risk factor and a property valuation riskfactor, said means for calculating combines each score generated by themeans for scoring each variance to calculate the numeric risk score;means for assigning a risk category to the loan based on the numericrisk score; and means for generating a computer screen for displayingthe numeric risk score and the risk category to a user.
 2. The automatedloan risk assessment system of claim 1, wherein the risk calculationmeans comprises: means for calculating a fraud risk score; means forcalculating an underwriting risk score; and means for calculating aproperty valuation score, wherein the numeric risk score for the loan isbased on at least two of the fraud risk score, the underwriting riskscore and the property valuation risk score.
 3. The automated loan riskassessment system of claim 2, wherein the fraud risk score calculationmeans comprises: means for storing general information about borrowersand properties; and means for detecting one or more variances among theloan information or between the loan information and the generalinformation, each variance having a certain degree, such that the fraudrisk score is based on the detected variances and the degrees thereof.4. The automated loan risk assessment system of claim 3, furthercomprising means for calculating a variance score for each detectedvariance based on the degree thereof, wherein the fraud risk scorerepresents the sum of the variance scores.
 5. The automated loan riskassessment system of claim 3, further comprising means for determiningone or more steps needed to resolve the plurality of variances.
 6. Theautomated loan risk assessment system of claim 3, further comprisingmeans for tracking the status of the plurality of variances.
 7. Theautomated loan risk assessment system of claim 2, wherein theunderwriting risk score calculation means comprises means for obtainingthe underwriting risk score from an underwriting risk score provider,and wherein the property valuation risk score calculation meanscomprises means for obtaining a property valuation risk score from aproperty valuation score provider.
 8. The automated loan risk assessmentsystem of claim 2, further comprising means for converting at least oneof the fraud risk score, the underwriting risk score and the propertyvaluation risk score.
 9. The automated loan risk assessment system ofclaim 8, wherein the means for converting comprises means for weightingat least one of the fraud risk score, the underwriting risk score andthe property valuation risk score based on a level of risk associatedtherewith such that the risk score is based on the weights assignedthereto.
 10. The automated loan risk assessment system of claim 8,wherein the means for converting comprises converting at least one ofthe fraud risk score, the underwriting risk score and the propertyvaluation risk score such that all of the scores are compatible, andwherein the numeric risk score represents an average of the compatiblescores.
 11. The automated loan risk assessment system of claim 1,wherein the loan information includes insurance information related toat least one insurance claim being asserted against an insurance policyto which a loan is subject, and wherein the means for calculating anumeric risk score comprises means for calculating a numeric risk scorefor the claim based on a plurality of risk factors including at leastone of a fraud risk factor, an underwriting risk factor and a propertyvaluation risk factor.
 12. The automated loan risk assessment system ofclaim 1, further comprising means for interfacing at least one pricingscheme of a loan service provider such that a loan or an insurancepolicy for a loan is automatically priced based on the numeric riskscore calculated therefor.
 13. The automated loan risk assessment systemof claim 1, wherein the numeric risk score is based on a combination ofthe fraud risk score factor, the underwriting risk factor and theproperty valuation risk factor.
 14. An automated loan risk assessmentsystem, comprising: a mechanism configured to receive information abouta loan; a mechanism configured to detect a plurality of variancesassociated with the information about the loan; a mechanism configuredto calculate a numeric risk score for the loan based on a plurality ofrisk factors including at least two of a fraud risk factor, anunderwriting risk factor and a property valuation risk factor, saidmechanism configured to calculate the numeric risk score by combiningeach score generated by the mechanism configured to score each varianceto calculate the numeric risk score; a mechanism for assigning a riskcategory to the loan based on the numeric risk score; and a mechanismfor generating a computer screen for displaying the numeric risk scoreand the risk category to a user.
 15. The automated loan risk assessmentsystem of claim 14, wherein the risk calculation mechanism comprises: amechanism configured to calculate a fraud risk score; a mechanismconfigured to calculate an underwriting risk score; and a mechanismconfigured to calculate a property valuation score, wherein the numericrisk score for the loan is based on at least two of the fraud riskscore, the underwriting risk score and the property valuation riskscore.
 16. The automated loan risk assessment system of claim 15,wherein the fraud risk score calculation mechanism comprises: amechanism configured to store general information about borrowers andproperties; and a mechanism configured to detect one or more variancesamong the loan information or between the loan information and thegeneral information, each variance having a certain degree, such thatthe fraud risk score is based on the detected variances and the degreesthereof.
 17. The automated loan risk assessment system of claim 16,further comprising a mechanism configured to calculate a variance scorefor each detected variance based on the degree thereof, wherein thefraud risk score represents the sum of the variance scores.
 18. Theautomated loan risk assessment system of claim 16, further comprising amechanism configured to determine one or more steps needed to resolvethe one or more detected variances.
 19. The automated loan riskassessment system of claim 16, further comprising means for tracking thestatus of the one or more detected variances.
 20. The automated loanrisk assessment system of claim 15, wherein the underwriting risk scorecalculation mechanism comprises a mechanism configured to obtain theunderwriting risk score from an underwriting risk score provider, andwherein the property valuation risk score calculation mechanismcomprises a mechanism configured to obtain a property valuation riskscore from a property valuation score provider.
 21. The automated loanrisk assessment system of claim 15, further comprising a mechanismconfigured to convert at least one of the fraud risk score, theunderwriting risk score and the property valuation risk score.
 22. Theautomated loan risk assessment system of claim 21, wherein theconverting mechanism comprises a mechanism configured to weight at leastone of the fraud risk score, the underwriting risk score and theproperty valuation risk score based on a level of risk associatedtherewith such that the risk score is based on the weights assignedthereto.
 23. The automated loan risk assessment system of claim 21,wherein the converting mechanism is configured to convert at least oneof the fraud risk score, the underwriting score and the propertyvaluation risk score such that all of the scores are compatible, andwherein the numeric risk score represents an average of the compatiblescores.
 24. The automated loan risk assessment system of claim 14,wherein the loan information includes insurance information related toat least one insurance claim being asserted against an insurance policyto which a loan is subject, and wherein the mechanism for calculating athe numeric risk score comprises a mechanism configured to calculate anumeric risk score for the claim based on a plurality of risk factorsincluding at least one of a fraud risk factor, an underwriting riskfactor and a property valuation risk factor.
 25. The automated loan riskassessment system of claim 14, further comprising a mechanism configuredto interface at least one pricing scheme of a loan service provider suchthat a loan or an insurance policy for a loan is automatically pricedbased on the numeric risk score calculated therefor.
 26. The automatedloan risk assessment system of claim 14, wherein the numeric risk scoreis based on a combination of the fraud risk score, the underwriting riskscore and the property valuation risk score.
 27. A non-transitorycomputer-readable medium whose contents cause a computer system toassess the risk associated with funding or insuring a loan by performingthe steps of: receiving information about a loan; detecting a pluralityof variances associated with the information about the loan; scoringeach variance detected by the computer system; calculating at thecomputer system a numeric risk score for the loan based on a pluralityof risk factors including at least two of a fraud risk factor, a creditrisk factor and a property valuation risk factor by combining each scorefor each variance detected by the computer system to calculate thenumeric risk score; assigning at the computer system a risk category tothe loan based on the numeric risk score; and displaying a computerscreen to a user which includes the numeric risk score and the riskcategory.
 28. The computer-readable medium of claim 27, wherein the stepof calculating the numeric risk score further comprises the steps of:calculating a fraud risk score; calculating an underwriting risk score;and calculating a property valuation score, wherein the numeric riskscore for the loan is based on the fraud risk score, the underwritingrisk score and the property valuation risk score.
 29. Thecomputer-readable medium of claim 28, wherein the step of calculatingthe fraud risk score comprises: storing general information aboutborrowers and properties; and detecting one or more variances among theloan information or between the loan information and the generalinformation, each variance having a certain degree, such that the fraudrisk score is based on the detected variances and the degrees thereof.30. The computer-readable medium of claim 29, further comprising thestep of calculating a variance score for each detected variance based onthe degree thereof, wherein the fraud risk score represents the sum ofthe variance scores.
 31. The computer-readable medium of claim 29,further comprising the step of determining one or more steps needed toresolve the plurality of variances.
 32. The computer-readable medium ofclaim 29, further comprising the step of tracking the status of theplurality of variances.
 33. The computer-readable medium of claim 28,wherein the step of calculating the underwriting risk score comprisesobtaining the underwriting risk score from an underwriting risk scoreprovider, and wherein the step of calculating the property valuationrisk score comprises obtaining a property valuation risk score from aproperty valuation score provider.
 34. The computer-readable medium ofclaim 28, further comprising the step of converting at least one of thefraud risk score, the underwriting risk score and the property valuationrisk score.
 35. The computer-readable medium of claim 34, wherein thestep of converting comprises weighting at least one of the fraud riskscore, the underwriting risk score and the property valuation risk scorebased on a level or risk associated therewith such that the numeric riskscore is based on the weights assigned thereto.
 36. Thecomputer-readable medium of claim 34, wherein the step of convertingcomprises converting at least one of the fraud risk score, theunderwriting risk score and the property valuation risk score such thatall of the scores are compatible, and averaging the compatible scores.37. The computer-readable medium of claim 27, wherein the loaninformation includes insurance information related to at least oneinsurance claim being asserted against an insurance policy to which aloan is subject, and wherein the medium further comprises the step ofcalculating a numeric risk score for the claim based on a plurality ofrisk factors including at least one of a fraud risk factor, anunderwriting risk factor and a property valuation risk factor.
 38. Thecomputer-readable medium of claim 27, further comprising the step ofinterfacing at least one pricing scheme of a loan service provider suchthat a loan or an insurance policy is automatically priced based on thenumeric risk score calculated therefor.
 39. The computer-readable mediumof claim 27, wherein the numeric risk score is based on a combination ofthe fraud risk score, the underwriting risk score and the propertyvaluation risk score.
 40. A computer-implemented method of assessing therisk associated with the funding or insuring of a loan, comprising:receiving information about a loan at a computer system; detecting usingthe computer system a plurality of variances associated with theinformation about the loan; scoring each variance detected by thecomputer system; calculating at a computer system a numeric risk scorefor the loan based on a plurality of risk factors including at least twoof a fraud risk factor, an underwriting risk factor and a propertyvaluation risk factor by combining each score for each variance detectedby the computer system to calculate the numeric risk score; assigning atthe computer system a risk category to the loan based on the numericrisk score; and displaying a computer screen to a user which includesthe numeric risk score and the risk category.
 41. Thecomputer-implemented method of claim 40, wherein the step of calculatingthe numeric risk score further comprises the steps of: calculating afraud risk score; calculating an underwriting risk score; andcalculating a property valuation score, wherein the numeric risk scorefor the loan is based on the fraud risk score, the underwriting riskscore and the property valuation risk score.
 42. Thecomputer-implemented method of claim 41, wherein the step of calculatingthe fraud risk score comprises: storing general information aboutborrowers and properties; and detecting one or more variances among theloan information or between the loan information and the generalinformation, each variance having a certain degree, such that the fraudrisk score is based on the detected variances and the degrees thereof.43. The computer-implemented method of claim 42, further comprising thestep of calculating a variance score for each detected variance based onthe degree thereof, wherein the fraud risk score represents the sum ofthe variance scores.
 44. The computer-implemented method of claim 42,further comprising the step of determining one or more steps needed toresolve the plurality of variances.
 45. The computer-implemented methodof claim 42, further comprising the step of tracking the status of theplurality of variances.
 46. The computer-implemented method of claim 41,wherein the step of calculating the underwriting risk score comprisesobtaining a credit risk score from a credit risk score provider, andwherein the step of calculating the property valuation risk scorecomprises obtaining a property valuation risk score from a propertyvaluation score provider.
 47. The computer-implemented method of claim41, further comprising the step of converting at least one of the fraudrisk score, the underwriting risk score and the property valuation riskscore.
 48. The computer-implemented method of claim 47, wherein the stepof converting comprises weighting at least one of the fraud risk score,the underwriting risk score and the property valuation risk score basedon a level of risk associated therewith such that the risk score isbased on the weights assigned thereto.
 49. The computer-implementedmethod of claim 47, wherein the step of converting comprises convertingat least one of the fraud risk score, the underwriting risk score andthe property valuation risk score such that all of the scores arecompatible, and averaging the compatible scores.
 50. Thecomputer-implemented method of claim 40, wherein the loan informationincludes insurance information related to at least one insurance claimbeing asserted against an insurance policy to which the loan is subject,and wherein the step of calculating a numeric risk score comprisescalculating a numeric risk score for the claim based on a plurality offactors including at least one of a fraud risk factor, an underwritingrisk factor, and a property valuation risk factor.
 51. Thecomputer-implemented method of claim 41, further comprising the step ofinterfacing at least one pricing scheme of a loan service provider suchthat a loan or insurance policy is automatically priced based on thenumeric risk score calculated therefor.
 52. The computer-implementedmethod of claim 41, wherein the numeric risk score is based on acombination of the fraud risk score, the underwriting risk score, andthe property valuation risk score.